Forecasting the Type of Audit Opinions: A Data Mining Approach

Data mining methods can be used to assist auditors with providing audit opinions. The purpose of this research is to forecast the type of audit opinions using data mining methods and compare the performance of these methods. Artificial neural networks, support vector machines, nearest neighbors and decision tree methods were used to conduct the research. The sample consists of 842 observations between 2001 and2010. The observations were divided in two groups: one group for training and the other for assessment of the method. A comparison of the performance of methods indicates that support vector machines approach outperforms the other approaches with a predictive ability of 76%. Also measuring type I and type II error rates of each method shows that the performance of support vector machines is higher than the other methods.